BOOKS OF RtfiDIfGS - PAHO/WHO

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~HNCOCK Fig. 1. Daily census with and without call-ins.
ET AL
Without Coll-in$-
45 - Census Mean , 172.63
Census Standard Devioation · 11.459
40 - With Co'l-ins
Census Mean*187.85
35 - Census Standard DeviQtion 5.956
25 -
z II,
120o
¡40 'N45 150 ¡55 160 .t65 170 175 180 185 190 195 200
CENSUS
the number of empty beds equals the CRA. If the number of empty
beds is less than the CA, scheduled admissions are cancelled until the
number of empty beds equals the CA. Thus the census at the decision
point is always between the CRA and the CA. The overall effect
of these allowances is to reduce significantly the variance in the hospital
census and thus increase the attainable occupancy while maintaining
a given turnaway level.
Reduction of census variance through use of the call-in algorithm
is the mechanism that allows the ASCS to achieve high average occupancies.
This census variance reduction is illustrated in Fig. 1, which
shows two separate simulation runs in which the numbers of scheduled
and emergency patients admitted are equal. It is apparent that a
facility using the call-in algorithm will operate at a higher average
occupancy and with lower census variance than a unit without callins.
In addition, a facility using the call-in algorithm will be at its
bed capacity (200 beds in Fig. 1) much more often than a facility without
call-ins.
Probability Distributions of Emergency Arrivals
and Patient Lengths of Stay
In order to simulate the randomness of a hospital, it is necessary
to assign a probability density function to emergency arrivals and to
patient length of stay. The Poisson distribution is used here to model
HEALTH emergency arrivals. This has been done often and has been found to
E VEICRS be a good fit to empirical daily emergency arrival distributions [8,9]
as well as being theoretically appealing. In the simulation model, a
day is divided into two periods. The first period extends from the